af Sandeberg et al. Health and Quality of Life Outcomes 2010, 8:109
http://www.hqlo.com/content/8/1/109
RESEARCH
Open Access
Psychometric properties of the DISABKIDS
Chronic Generic Module (DCGM-37) when used in
children undergoing treatment for cancer
Margareta af Sandeberg1,2*, Eva M Johansson3, Peter Hagell4, Lena Wettergren1
Abstract
Background: The aim was to evaluate data quality and psychometric properties of an instrument for measurement
of health-related quality of life: DISABKIDS Chronic Generic Module (DCGM-37) used in school-aged children with
cancer.
Methods: All school-children diagnosed with cancer in Sweden during a two-and-a-half year period were invited
to participate in the study. Analysis was performed on combined data from two assessments, two and-a-half and
five months after start of cancer treatment (n = 170). The instrument was examined with respect to feasibility, data
quality, reliability and construct and criterion-based validity.
Results: Missing items per dimension ranged from 0 to 5.3 percent, with a majority below three percent.
Cronbach’s alpha values exceeded 0.70 for all dimensions. There was support for the suggested groupings of items
into dimensions for all but six of the 36 items of the DCGM-37 included in this study. The instrument discriminated
satisfactorily between diagnoses reflecting treatment burden.
Conclusions: The results indicate satisfactory data quality and reliability of the DCGM-37 when used in children
undergoing treatment for cancer. Evaluation of construct validity showed generally acceptable results, although not
entirely supporting the suggested dimensionality. Continued psychometric evaluation in a larger sample of children
during and after treatment for cancer is recommended.
Background
It is known that treatment for cancer during childhood
may cause physical, social and emotional concerns and
thus have an impact on health-related quality of life
(HRQOL) [1]. Results from studies that have followed
HRQOL in children during cancer treatment reveal
emotional distress [2,3], diminished physical function
and status [2,4] as well as symptoms related to disease
and treatment [4,5] during the first year following
diagnosis.
There are only a few available valid instruments for
assessment of HRQOL in children and adolescents with
cancer. One instrument commonly used among these
individuals is the Pediatric Quality of Life Inventory
(PedsQL) including a generic scale and a disease-specific
* Correspondence: [email protected]
1
Department of Neurobiology, Care Sciences and Society, Karolinska
Institutet, Huddinge, Sweden
Full list of author information is available at the end of the article
cancer module [6]. The generic scale was developed to
measure HRQOL in healthy populations as well as
patient populations in four dimensions. The diseasespecific cancer module consists of 27 items encompassing eight dimensions. Psychometric evaluation of the
PedsQL generic and cancer module has shown satisfactory results and the instrument is recommended as an
outcome measure in research as well as in clinical practice for assessment of HRQOL [6]. Another instrument
used among children with cancer is the revised Memorial Symptom Assessment Scale (MSAS) for children aged
seven to 12 years [7]. The MSAS is a self-report questionnaire which assesses presence, frequency, severity
and associated distress with established cancer-related
symptoms. Evaluation of the reliability and validity of
the MSAS has shown that children with cancer as young
as seven years can report clinically relevant and consistent information about their symptom experience [7].
Follow-up studies after cancer treatment have commonly
© 2010 af Sandeberg et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative
Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and
reproduction in any medium, provided the original work is properly cited.
af Sandeberg et al. Health and Quality of Life Outcomes 2010, 8:109
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used generic and domain specific instruments developed
for an adult population such as the Short Form Survey
(SF-36) [2], the TNO-AZL Children’s Quality of Life
(TACQOL) [3] and Hospital Anxiety and Depression
scale (HADS) [2]. These instruments also provide validated normative data for adolescents and young adults
in the general population [8]. Among the instruments
mentioned above only PedsQL include items concerning
school.
An instrument which includes social issues is the
DISABKIDS Chronic Generic Module (DCGM-37)
developed in recent years in collaboration with partners from seven European countries [9]. The instrument was developed for assessment of HRQOL in
children and adolescents suffering from chronic conditions and addresses aspects that pertain not to specific
conditions but to general aspects from the perspectives
of children and adolescents [10]. The DISABKIDS consists of four versions: a self-report version for children,
a proxy version for parents and a child and proxy version for those younger than eight years (The DISABKIDS - Smileys measure). The long version children
self-report DCGM-37 measures HRQOL in six dimensions (Independence, Physical Limitation, Emotion,
Social Exclusion, Social Inclusion, and Treatment).
Results from pilot testing of the DCGM-37 in children
with different chronic conditions have denoted satisfactory internal consistency for all dimensions with
Chronbach’s alpha coefficient ranging from 0.70 to
0.87 [10,11]. Construct validity evaluated by factor analysis, as well as convergent and discriminant validity
have also shown satisfactory results in pilot testing of
the instrument [11].
In a recent national study our research group followed
HRQOL, school attendance and social interaction with
friends in a cohort of Swedish school-children (n = 101)
starting treatment for cancer [12]. The DCGM-37 was
chosen for assessment of HRQOL as it included relevant
items regarding social issues such as school and friends
as well as treatment-related issues and was available in
the Swedish language [13]. Participants were assessed
twice during the first five months of cancer treatment.
The results indicated a diminished HRQOL compared
to children with chronic conditions over the study period, with girls rating worse HRQOL than boys [12].
Self-reported HRQOL was positively correlated to days
of school attendance. Although these results suggest
that the DCGM-37 is useful in children undergoing cancer treatment, it has not been tested regarding its psychometric properties and relevance in this target group
before. The aim of this study was to evaluate data quality and psychometric properties of the DCGM-37
among school-aged children with cancer.
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Methods
The DCGM-37 was completed at two assessment points
approximately two-and-a-half (T1) and five months (T2)
after the start of treatment for cancer. These two assessments are part of a larger study following a cohort of
school children regarding social life up to six years after
diagnosis.
Sample
All children in Sweden attending compulsory school
grades 1-9 (aged seven to 16 years), newly diagnosed
with cancer and starting chemotherapy and/or radiation
therapy during the period January 2004 to May 2006
were eligible for inclusion in the study [12]. Children
who were scheduled to undergo early stem cell transplantation, children with brain tumors exclusively treated with surgery, and children from families that were
not able to speak or read Swedish were excluded. One
hundred and forty-five children and adolescents were
invited to participate in the larger study including three
assessments during the first six months of treatment
and 101 participated in all the assessments. The second
(T1) and third (T2) assessments included the DCGM-37
or the Smiley version. Two participants did, due to
organizational reasons not complete the DCGM-37 at
T1; eleven participants completed the Smiley version at
T1 and ten at T2. Those who completed the DCGM-37
at T1 (n = 83) and T2 (n = 87) were included in this
report.
DCGM-37
The DCGM-37 self-report version for children was used
[10]. Those children not considered able to complete
the DCGM-37 were approached with the Smiley version
developed for those younger than eight years. As the
majority of the participating children filled out the long
version (DCGM-37), the results from the Smiley version
are not included in this report. DCGM-37 consists of
six dimensions: Independence (autonomy and living
without impairments), Physical Limitation (functional
limitations, perceived health), Emotions (emotional worries and concerns), Social Exclusion (stigma, feeling left
out), Social Inclusion (acceptance of others, positive
relationships) and Treatment (perceived emotional
impact of treatment). Each dimension consists of six
items and refers to the four previous weeks. All items
have five-grade verbal response options ranging from 1
(never) to 5 (very often). Within each scale, item raw
scores are summed and transformed into a scale from 0
(worst possible HRQOL) to 100 (best possible HRQOL),
following the standard scoring algorithms of the instrument [10]. Missing values were substituted if all but one
of the items within a dimension was responded to,
af Sandeberg et al. Health and Quality of Life Outcomes 2010, 8:109
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meaning, a person-specific mean score was calculated
based on the existing answers [11].
Procedure
The instructions given to the families emphasized the
importance of the DCGM-37 being filled out by the
child, with support only if required [12]. Children who
met the inclusion criteria and their parents were contacted by the consultant nurse in pediatric oncology to
receive oral and written information about the study.
Informed consent was obtained from those children
willing to participate and their parents. The DCGM-37
along with a study-specific questionnaire and a stamped
return envelope were given to each hospitalized participant or sent home to participants who were not hospitalized. Ethical approval was obtained from the Regional
Ethical Review Board in Stockholm (03-662, 04-208).
To evaluate feasibility seven consultant nurses in
pediatric oncology were asked to give their opinions on
the items included in the DCGM-37 in a group session.
The consultant nurses were chosen because of their
expertise in the field, and they represent all pediatric
oncology centers in the country.
Data analyses
All statistical calculations were conducted using SPSS
version 16.0 (SPSS Inc, Chicago, IL). The psychometric
analyses are based on pooled data from T1 (n = 83) and
T2 (n = 87). Pooling of data is recommended when
sample sizes are limited in order to increase precision of
estimates [14,15].
Feasibility of the DCGM-37 was examined through the
nurses’ comments of the items as well as by oral and
written comments given by the participating children,
adolescents, and their parents.
Data quality was evaluated by examination of the
amount of missing item responses [14]. Up to 10% missing responses has been suggested as acceptable [16]. The
legitimacy of adding up items to generate total dimension scores was tested by examination of item means,
standard deviations and corrected item-total correlation
within each dimension. Simple summation of item
scores into a total score is considered supported when
item means and standard deviations within a dimension
are similar and corrected item-total correlation coefficients exceed 0.3 [14]. Furthermore, items within each
dimension should represent the same latent variable.
This is considered supported if corrected item-total correlations are ≥0.40 [14].
The distribution of dimension scores was examined by
calculations of means, standard deviations, and floor
and ceiling effects. Cronbach’s alpha values were calculated to estimate the internal consistency reliability of
the DCGM-37. Floor and ceiling effects should be less
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than 15% [17] and alpha values ≥0.70 are considered
acceptable whereas ≥0.80 are preferred [18].
Multi-trait-scaling analyses with correction for overlap
was performed to examine the internal construct validity
of the DCGM-37. This is supported when an item’s corrected item-total correlation is ≥0.40 with the dimension
it is hypothesised to belong to, while correlating weaker
with all other dimensions [19,20]. The proportion (%) of
items within each dimension that met these criteria was
examined and referred to as the scaling success rate.
To examine whether the six dimensions appear to
measure different aspects of HRQOL the correlation
coefficients between dimensions were compared with
each dimension’s internal consistency (Cronbach’s
alpha). If the alpha value of a dimension is higher than
the dimension’s correlation to the other dimensions, it
indicates that dimension scores represent different
aspects of HRQOL [14].
To evaluate criterion-based validity the instrument’s
capacity to discriminate between patients differing in
symptom burden, data from children diagnosed with
acute lymphoblastic leukemia (ALL) were compared to
those with sarcoma. In the pooled DCGM-37 data of
170 children, 50 were undergoing treatment for ALL
and 32 for sarcoma. Children with ALL exclusively
receive chemotherapy and are often described by physicians and nursing staff as a group with fewer side effects
from treatment compared to other diagnoses. Children
with sarcomas receive combination therapy including
surgery, chemotherapy and radiation therapy and are
often described as a group with more side effects and
complications than other diagnoses [21]. In line with
this our previous report showed that children with
osteosarcoma were more likely to be absent from school
than those with other diagnoses [12]. Independent
t-tests were calculated to investigate potential differences in mean values for the DCGM-37 dimensions by
diagnosis (ALL vs. sarcoma) and age groups (7-12 years
vs. 13-16 years). Effect sizes (ES) were calculated to
highlight the clinical importance of potential mean value
differences. According to Cohen [22], ES = 0.20-0.50
indicates a small difference, ES = 0.51-0.80 indicates a
medium difference and ES > 0.80 indicates a large difference. P-values ≤ 0.05 were considered statistically
significant.
Results
Socio-demographic and clinical characteristics of the
sample are presented in table 1. Due to a negative reaction from parents, one of the items in the DCGM-37
(Item 17: “Do you have fears about the future because
of your condition?”) was excluded early in the study and
treated as a missing value for all participants. After the
exclusion of this item the majority of the participants
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Table 1 Socio-demographic characteristics of
participating children
Participants
T1
T2
Pooled data
Total number, n
83
87
170
47 (57)
50 (57)
97 (57)
36 (43)
37 (43)
73 (43)
12 (7-16)
12 (7-16)
12 (7-16)
7-12 years
43 (52)
44 (51)
87 (51)
13-16 years
40 (48)
43 (49)
83 (49)
School grade at diagnosis,
median (range)
6 (1-9)
6 (1-9)
6 (1-9)
Siblings living at home, n (%)
73 (88)
77 (88)
150 (88)
24 (29)
26 (30)
50 (29)
Sex, n (%)
Boys
Girls
Age at diagnosis, median (range)
Age groups, n (%)
Diagnoses, n (%)
Acute lymphoblastic
leukaemia
Acute myeloid leukaemia
4 (5)
5 (6)
9 (5)
CNSa tumours
13 (16)
13 (15)
26 (15)
Non - Hodgkin’s lymphoma
Hodgkin’s Lymphoma
11 (13)
8 (10)
10 (12)
9 (10)
21 (12)
17 (10)
Neuroblastoma
0
1 (1)
1 (1)
16 (19)
16 (18)
32 (19)
Rhabdomyosarcoma
4 (5)
4 (5)
8 (5)
Otherb
3 (3)
3 (3)
6 (4)
Sarcoma
a
Central nervous system.
Germ cells tumor, Soft tissue sarcoma (nerve), Sertoli leydig cell tumor,
Synovial sarcoma, Teratoma and a mixed tumor.
b
Page 4 of 7
filled out the instrument without reporting any problems. Some parents described that, prior to filling in
the questionnaire; they were worried that the items
would upset their children and make them doubtful
about the future. However, after completing the questionnaire together, some parents expressed appreciation
over the way the instrument opened up for deeper conversation with their offspring. Evaluation by seven consultant nurses in pediatric oncology, suggested that all
but one item was feasible. Item 30 (‘Do your friends
enjoy being with you?’) was questioned if appropriate in
the Swedish culture as it may not be fully accepted to
describe oneself in a very positive manner.
The percentage of missing items by dimension was
below six percent (range 0-5.3), the largest number of
missing items being found in the dimension Social
Exclusion (Table 2). Reasons for not responding to an
item were seldom reported. The reason for not answering items regarding school was occasionally explained
by the statement, “I have not been to school”. Items not
answered in the Treatment dimension were in some
cases explained by the statement “I am not taking any
medication”.
Item means and standard deviations within the respective dimensions were roughly equivalent (Table 2). All
but one corrected item-total correlation exceeded 0.30.
The corrected item-total for item 31 in the dimension
Social Inclusion was 0.28, and in all but six instances
(items 10, 11, 22, 26, 30, 31) the item-total correlation
was ≥0.40 (Table 2, Table 3).
Floor effects ranged between 0-2.4% (Table 2). Similarly, ceiling effects were between 0-2.9% with exception
for the Treatment dimension, which had a larger, still
acceptable effect of 10% (Table 2). Reliability for all
dimension scores exceeded the recommended criteria
Table 2 Descriptive and psychometric statistics for the DCGM-37 in Swedish children on cancer treatment, pooled
data, n = 170
Dimensions
n
Mean
(SD)
Missing
items,
range
(%)
Ranges of
item mean
(SD)
Floor/
Ceiling
effect
(%)
Independence 170
60.4
(19.5)
0-4 (0)
3.03-3.89
(0,96-1,18)
0.6/0
0.81
0.43-0.68
0.15-0.60
93
Physical
Limitation
169
53.1
(19.6)
0-2 (0.6)
3.25-3.94
(1,02-1,34)
0/0
0.76
0.32-0.66
0.19-0.58
87
Emotion
165
58.5
(19.9)
3-5 (2.9)
2.88-3.53
(0,97-1,22)
0/1.2
0.84
0.54-0.70
0.25-0.65
100
Social
exclusion
161
68.5
(17.7)
1-13 (5.3)
3.31-4.51
(0,68-1,22)
0/2.9
0.76
0.35-0.63
0.09-0.60
90
Social
inclusion
168
61.9
(17.3)
0-6 (1.2)
3.02-4.35
(0,83-1,16)
0/0.6
0.71
0.28-0.66
-0.01-0.65
73
Treatment
164
64.0
(25.8)
4-8 (3.5)
3,35-4.02
(1,14-1,60)
2.4/10.0
0.87
0.54-0.77
0.14-0.47
100
Reliability Item-to-own
Item-to-other
(a)
dimension correlation dimension correlation
(range)
(range)
Scaling
success
(%) a
a
Number of item-to-other dimension correlations that are stronger than the corrected item-total correlation within a dimension/Total number of discriminant
validity tests (i.e., number of items × number of dimensions minus 1), expressed as a percentage.
af Sandeberg et al. Health and Quality of Life Outcomes 2010, 8:109
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Table 3 Multitrait-scaling analysis of the DCGM-37,
pooled data (n = 170)
(1) Independence
(2) Physical Limitation
(3) Emotion
(4) Social Exclusion
(5) Social Inclusion
Item
(1)
(2)
(3)
(4)
(5)
(6)
1
0.43a
0.29
0.39
0.35
0.34
0.23
2
0.56
0.36
0.48
0.38
0.48
0.38
3
0.66
0.59
0.48
0.41
0.56
0.17
4
0.63
0.49
0.51
0.52
0.46
0.23
5
0.68
0.60
0.53
0.46
0.55
0.20
6
0.50
0.55d
0.37
0.31
0.58d
0.15
7
0.57
0.50
0.36
0.36
0.58d
0.20
8
0.49
0.66
0.57
0.51
0.49
0.22
9
0.55
0.58
0.53
0.47
0.54
0.25
10
0.29
c
0.32
0.31
d
0.34
d
0.36
0.31
11
0.26
0.37c 0.33
0.40d
0.28
0.19
12
0.49
0.59
0.48
0.54
0.51
0.28
13
0.43
0.39
0.63
0.57
0.25
0.41
14
0.52
0.51
0.70
0.59
0.41
0.42
15
0.41
0.47
0.60
0.51
0.43
0.25
16
0.37
0.38
0.56
0.44
0.33
0.34
18
0.62
0.62
0.67
0.65
0.51
0.39
19
0.40
0.48
0.54
0.42
0.46
0.40
20
0.55
0.55
0.60
0.63
0.53
0.32
21
0.27
0.35
0.35
0.45
0.23
0.34
22
0.30
0.43d 0.42d 0.34c
0.30
0.09
23
0.29
0.31
0.37
0.42
0.32
0.29
24
0.33
0.43
0.48
0.53
0.34
0.25
d
25
0.50
0.46
0.60
0.51
0.40
0.31
26
0.34d
0.30
0.39d 0.42d
0.31c
0.17
27
0.52
0.56
0.36
0.35
0.66
0.21
28
d
0.62
d
0.61
0.44
0.39
0.60
0.25
29
0.56
d
0.65d
0.43
0.38
0.52
0.31
0.21
0.21
0.31d
0.31c
-0.01
0.26
0.24
0.16
0.28b,c 0.26
30
31
(6) Treatment
0.26
0.29
d
32
0.21
0.27
0.31
0.25
0.26
0.49
33
0.16
0.29
0.40
0.37
0.22
0.69
34
0.36
0.37
0.41
0.42
0.35
0.54
35
0.14
0.21
0.39
0.29
0.16
0.77
36
0.25
0.22
0.35
0.24
0.22
0.77
37
0.34
0.37
0.47
0.39
0.35
0.71
a
Corrected item-total (item-to-item-within-own-dimension) correlations are in
bold.
b
Corrected item-total correlations failing to meet the ≥0.30 criterion.
c
Corrected item-total correlations failing to meet the ≥0.40 criterion.
d
Item-to-other-dimension correlation exceeding the corrected item-total
correlation (scaling failure).
minimum of 0.70 and three exceeded the preferred
value of 0.80 (Table 2).
Multi-trait scaling analyses supported the grouping of
items into dimensions for 26 of the 36 items as their corrected item-total correlations exceeded the correlations
Page 5 of 7
with other dimension scores; scaling success rates ranging between 73-100% (Table 2, Table 3).
Internal consistencies for all dimensions were larger
than their correlation coefficients to the other dimensions
(Table 4). This suggests that the six dimension scores
represent distinct constructs. However, the alpha values
for the Social Inclusion dimension (0.71) was only marginally above this dimension’s correlation with the Independence (0.68) and Physical Limitation dimensions (0.69),
suggesting some overlap. Similarly, the alpha value for the
Social Exclusion dimension (0.76) was relatively close to
its correlation with the Emotion dimension (0.71).
Mean values by age groups (7-12 years vs. 13-16
years) are presented in Table 5. HRQOL did not differ
between the two age groups with one exception, Physical Limitation was rated significantly higher among the
13-16-years-olds compared to the younger group. Effect
sizes were all low or medium (Table 5).
Mean value differences and effect sizes between ALL
and sarcoma are presented in Table 6. Patients with sarcoma scored significantly lower than those with ALL in
all dimensions. Effect sizes were all large (Table 6).
Discussion
This study assessed the data quality and psychometric
properties of the DCGM-37 in a sample of Swedish
school-aged children receiving treatment for cancer. The
instrument appears to be a feasible instrument with satisfactory data quality and generally acceptable psychometric
properties in children undergoing treatment for cancer.
Data quality was satisfying with overall acceptable
amount of missing values. Missing responses were primarily associated with the two school-related items,
mostly due to school absence. Missing data in the Treatment dimension was sometimes due to the respondent
not taking any medication at the time of completing the
questionnaire.
Summation of item scores into dimension scores without standardization or weighting was supported by similarity of means and standard deviations within
dimensions and item-total correlations exceeding 0.3
[14]. Similarly, reliability was acceptable or satisfying
and there were no abundant ceiling or floor effects. This
provides indirect support for the instrument’s sensitivity
and responsiveness [17]. Accordingly, all dimension
scores were able to discriminate between children with
ALL and sarcoma. We also scrutinized our results to
corresponding results collected from field studies of the
instrument to be able to make comparisons to other
diagnoses. Children undergoing treatment for cancer
rated their HRQOL as poorer in all dimensions compared to children with other chronic conditions [11].
It is promising that still, the DCGM-37 was able to discriminate patients with regard to treatment burden.
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Table 4 Inter-dimension correlations for DCGM-37, pooled data, n = 170
Independence
Physical Limitation
Emotion
Social Exclusion
Social Inclusion
(0.81)
Physical Limitation
0.67
Emotion
0.64
0.63
(0.84)
Social Exclusion
0.58
0.65
0.71
(0.76)
Social Inclusion
0.68
0.69
0.55
0.52
(0.71)
Treatment
0.31
0.36
0.50
0.41
0.33
a
Treatment
a
Independence
(0.76)
(0.87)
Internal consistency reliability (Cronbach’s alpha) is presented in parenthesis in the diagonal.
However, data also challenged the interpretability of
some dimension scores as item-total correlations in
three dimensions (Physical Limitation, Social Exclusion,
Social Inclusion), were below 0.4, which is considered to
suggest that an item may not represent the same construct as the dimension [14,16]. Furthermore, scaling
success rates for all dimensions but Emotion and Treatment indicated that the grouping of items into dimensions may not be optimal. With one exception (item 6)
scaling failure involved the Social Exclusion and Social
Inclusion dimensions.
Considering the six problematic items from the multitrait-scaling analyses, one may speculate on possible
explanations for these findings in relation to the population of children undergoing cancer treatment. It appears
that the dimensionality regarding Physical Limitation
and the social dimensions (Social Inclusion, Social
Exclusion) are difficult to separate from one another. It
is reasonable that physical health and social life are
related to one another in persons undergoing heavy
treatment. Three of these items (item 10, 26, 31) concern the child’s perception of explaining the disease to
others. The result may represent a mixture of effects of
cancer treatment on all dimensions. Reasons for not
communicating with peers may be a result of physical
weakness giving social restrictions and be related to
both physical and social aspects. The results regarding
sleep difficulty (item 11) and problems concentrating
(item 22) may reveal the same physical/social interaction. Item 30 (‘Do your friends enjoy being with you?’)
in the dimension Social Inclusion, showed a moderate
correlation coefficient to Independence as well as to
Emotion and Social Exclusion. It is conceivable that this
item implies emotional worries and concerns as well as
the feeling of being left out, which may explain the
observed dimensional ambiguity related to this item.
Despite indications of scaling failure due to the items
discussed above, we consider them to be of great interest in a population of children and adolescents with
cancer [5]. The question that our observations raise,
however, is whether they are suitable representations of
the dimensions that they are suggested to belong to.
There are some limitations in the present study. The
sample size is considered small and includes heterogeneous cancer diagnoses. This is difficult to rectify as the
Swedish pediatric population diagnosed with cancer is,
for natural reasons, small. The authors of this paper
suggests continued psychometric evaluation of DCGM37 in a larger sample of children with cancer, preferably
in a Nordic multicenter study, including more conclusive analyses such as Rasch, item-response theory or
confirmatory factor analyses. A strength of the present
study is, however, that it is a nationwide study including
all children in Sweden diagnosed with cancer during a
two-and-a-half year period and that time for
Table 5 Differences in self-reported HRQOL between age
groups: 7-12 years (n = 87) and 13-16 years (n = 83),
pooled data
Table 6 Significant differences in self-reported HRQOL
between children on cancer treatment for Acute
lymphoblastic leukaemia (ALL) (n = 50) and Sarcoma
(n = 32), pooled data
DCGM-37 dimensions
7-12 years
13-16 years
Meana (SD)
Meana (SD)
P
ES
b
Independence
57.8 (19.5)
63.2 (19.2)
ns
0.28
Physical Limitation
50.0 (18.7)
56.3 (20.0)
<0.05
0.33
DCGM-37 dimensions
ALL
Sarcoma
Meana (SD)
Meana (SD)
P
66.3 (14.9)
56.9 (18.1)
44.0 (20.7)
37.4 (16.1)
< 0.001
< 0.001
ES
b
Emotion
57.8 (19.9)
59.3 (20.0)
ns
0.08
Independence
Physical Limitation
1.25
1.14
Social Exclusion
68.9 (17.7)
68.1 (17.8)
ns
0.05
Emotion
62.6 (18.5)
43.3 (14.2)
<0.001
1.18
74.6 (16.7)
52.8 (17.7)
<0.001
1.27
Social Inclusion
59.8 (16.7)
64.2 (17.8)
ns
0.25
Social Exclusion
Treatment
60.3 (26.0)
67.9 (25.1)
ns
0.30
Social Inclusion
62.4 (15.2)
48.3 (14.8)
<0.001
1.22
Treatment
64.2 (23.8)
44.1 (22.3)
<0.001
0.87
a
Scores range from 0 to 100, higher scores represent a better HRQOL
Differences tested by student’s unpaired t-test.
b
Effect size.
ns, non-significant.
a
Scores range from 0 to 100, higher scores represent a better HRQOL
Differences tested by student’s unpaired t-test.
b
Effect size.
af Sandeberg et al. Health and Quality of Life Outcomes 2010, 8:109
http://www.hqlo.com/content/8/1/109
assessments in relation to start of treatment is about the
same for all participants.
Conclusions
The results provided in this paper support feasibility,
and data quality as well as general support for the psychometric properties of the DCGM-37 when used in
children undergoing treatment for cancer. However the
dimensionality of the instrument is uncertain which may
impact score interpretability. Further psychometric evaluation in a large sample of children with cancer as well
as after pediatric cancer treatment is recommended to
better understand these aspects and provide firmer
conclusions.
Page 7 of 7
8.
9.
10.
11.
12.
13.
Acknowledgements
The authors thank the children and adolescents as well as their parents for
sharing information. Furthermore, the consultant nurses in childhood cancer
in Sweden are acknowledged for recruitment of participants and data
collection: Maria Renström, Eva Turup, Marie Sandgren, Karin Gustafsson,
Maria Olsson and Carina Mähl. This study was supported by grants from the
Swedish Childhood Cancer Foundation.
Author details
1
Department of Neurobiology, Care Sciences and Society, Karolinska
Institutet, Huddinge, Sweden. 2Department of Pediatric Oncology, The
Karolinska University Hospital, Stockholm, Sweden. 3Department of Medicine,
Karolinska Institutet, and Red Cross College University, Stockholm, Sweden.
4
Department of Health Sciences, Lund University, Sweden.
14.
15.
16.
17.
18.
19.
Authors’ contributions
Conception and design: MafS, LW and PH. Collection and assembly of data:
MafS. Data analysis and interpretation: MafS, LW and PH. First draft of the
manuscript: MafS. Critical revision: MafS, LW, PH and EJ. All authors read and
approved the final manuscript.
20.
21.
Competing interests
The authors declare that they have no competing interests.
22.
Received: 13 May 2010 Accepted: 28 September 2010
Published: 28 September 2010
References
1. Eiser E: Cancer. In Quality of life in child and adolescent illness: concepts,
methods, and findings. Edited by: Koot HM, Wallander JM. New York:
Brunner-Routledge, cop.; 2001:267-291.
2. Jörngården A, Mattsson E, von Essen L: Health-related quality of life,
anxiety and depression among adolescents and young adults with
cancer: a prospective longitudinal study. Eur J of Cancer 2007,
43(13):1952-8.
3. Landolt MA, Vollrath M, Niggli FK, et al: Health-related quality of life in
children with newly diagnosed cancer: a one year follow-up study.
Health Qual Life Outcomes 2006, 20(4):63.
4. Enskär K, Carlsson M, Golsäter M, Hamrin E, Kreuger A: Life situation and
problems as reported by children with cancer and their parents.
J Pediatr Oncol Nurs 1997, 14(3):18-26.
5. Hedström M, Ljungman G, von Essen L: Perceptions of distress among
adolescents recently diagnosed with cancer. J Pediatr Hem Oncol 2005,
27(1):15-22.
6. Varni JW, Burwinkle TM, Katz ER, Meeske K, Dickinson P: The PedQL in
Pediatric cancer: reliability and validity of the pediatric Quality of Life
Inventory Generic Core Scales, Multidimensional Fatigue Scale, and
Cancer Module. Cancer 2002, 94(7):2090-106.
7. Collins JJ, Devine TD, Dick GS, Johnson EA, Kilham HA, Pinkerton CR, et al:
The measurement of symptoms in young children with cancer: the
validation of the memorial symptom assessment scale in children aged
7-12. J Pain Sympt Man 2002, 19(59):363-77.
Jörngården A, Wettergren L, von Essen L: Measuring health-related quality
of life in adolescents and young adults: Swedish normative data for the
SF-36 and the HADS, and the influence of age, gender, and method of
administration. Health Qual Life Outcomes 2006, 4(1):91.
Bullinger M, Schmidt S, Petersen C, DISABKIDS Group: Assessing quality of
life of children with chronic health conditions and disabilities: a
European approach. Int J Rehab Res 2002, 25(3):197-206.
The European DISABKIDS Group: The DISABKIDS questionnaires: Quality of
life questionnaires for children with chronic conditions. Lengerich: Pabst
Science Publishers 2006.
Simeoni MC, Schmidt S, Muehlan H, Debensason D, Bullinger M, DISABKIDS
Group: Field testing of a European quality of life instrument for children
and adolescents with chronic conditions: the 37-item DISABKIDS Chronic
Generic Module. Qual Life Res 2007, 16(5):881-93.
af Sandeberg M, Johansson E, Björk O, Wettergren L: Health-related quality
of life relates to school attendance in children on treatment for cancer.
J Pediatr Oncol Nurs 2008, 25(5):265-74, Epub 2008 Jul 22.
Chaplin JE, Hanas R, Lind A, Tollig H, Wramner N, Lindblad B: Assessment
of childhood diabetes-related quality-of-life in west Sweden. Acta
Paediatr 2008, 98(2):361-6.
Ware JE Jr, Gandek B: Methods for testing data quality, scaling
assumptions, and reliability: the IQOLA Project approach. J Clin Epidemiol
1998, 51(11):945-52.
Westen , Weinberger : When clinical description becomes statistical
prediction. Am Psychol 2004, 59:595-613.
Saris-Baglama RN, Dewey CJ, Chisholm GB, Kosinski M, Bjorner JB, Ware JR
Jr: SF health outcomes™ scoring software user’s guide. Lincoln: Quality
Metric, Inc. 2004.
McHorney CA, Tarlov AR: Individual-patient monitoring in clinical practice:
are available health status surveys adequate? Qual Life Res 1995,
4(4):293-307.
Nunnally JC, Bernstein IH: Psychometric theory. New York: McGraw-Hill, 3
1994.
Fayers P, Machin D: Quality of life - Assessment, Analysis and
Interpretation of patient reported outcomes. Chichester: John Wiley &
Sons Ltd 2007, (ISBN 047002).
Ware JR Jr, Harris WJ, Gandek B, Rogers BW, Reese PR: MAP-R for Windows:
Multitrait/multi-item analysis program - revised user’s guide. Boston: MA:
Health Assessment Lab 1997, 2-31.
Betcher DL, Simon PJ, McHard KM: Bone tumors. In Nursing care of children
& adolescents with cancer. Edited by: Baggott C, Patterson Kelly K, Fochtman
D, Foley G. Philadelphia: W.B. Saunders company; , 3 2002:575-588.
Cohen J: Statistical power analysis for the behavioral sciences. Hillsdale,
NJ: Lawrence Erlbaum Associates, 2 1988.
doi:10.1186/1477-7525-8-109
Cite this article as: af Sandeberg et al.: Psychometric properties of the
DISABKIDS Chronic Generic Module (DCGM-37) when used in children
undergoing treatment for cancer. Health and Quality of Life Outcomes
2010 8:109.
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